一种识别电报中人格特征的方法

M. Shayegan, Mohaddese Valizadeh
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引用次数: 2

摘要

获取人们的个性特征一直是一项具有挑战性的任务。另一方面,基于行为数据获取人格特征是人类日益增长的兴趣之一。大量研究表明,人们在社交网络上花费大量时间,并在网络空间中表现出一些创造个性模式的行为。其中一个在包括伊朗在内的一些国家受到广泛欢迎的社交网络是Telegram。这项研究的基础是根据用户在Telegram上的行为自动识别他们的个性。为此,收集Telegram群组用户的信息,然后根据著名的NEO personality Inventory (NEO PI-R)识别每个成员的性格特征。在人格分析方面,本研究采用了三种方法,包括;余弦相似度,贝叶斯和MLP算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Method for Identifying Personality Traits in Telegram
Accessing people’s personality traits has always been a challenging task. On the other hand, acquiring personality traits based on behavioral data is one of the growing interests of human beings. Numerous researches showed that people spend a lot of time on social networks and show behaviors that create some personality patterns in cyberspace. One of these social networks that have been widely welcomed in some countries, including Iran, is Telegram. The basis of this research is automatically identifying users’ personalities based on their behavior on Telegram. For this purpose, messages from Telegram group users are collected, and then the personality traits of each member according to the famous NEO Personality Inventory (NEO PI-R) are identified. For personality analysis, the study employed three methods, including; Cosine Similarity, Bayes, and MLP algorithms.
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